Modeling Population Growth in R with the biogrowth Package

Modeling Population Growth in R with the biogrowth Package

: kinetic modelling, model fitting, predictions, dynamic modeling, R, predictive microbiology, uncertainty

The growth of populations is of interest in a broad variety of fields, such as epidemiology, economics or biology. Although a large variety of growth models are available in
the scientific literature, their application usually requires advanced knowledge of mathematical programming and statistical inference, especially when modelling growth under
dynamic environmental conditions. This article presents the biogrowth package for R,
which implements functions for modelling the growth of populations. It can predict growth
under static or dynamic environments, considering the effect of an arbitrary number of
environmental factors. Moreover, it can be used to fit growth models to data gathered
under static or dynamic environmental conditions. The package allows the user to fix
any model parameter prior to the fit, an approach that can mitigate identifiability issues
associated to growth models. The package includes common S3 methods for visualization
and statistical analysis (summary of the fit, predictions, . . . ), easing result interpretation.
It also includes functions for model comparison/selection. We illustrate the functions in
biogrowth using examples from food science and economy.

Alberto Garre

https://www.jstatsoft.org/article/view/v107i01

Wageningen University & Research

September 2023

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